Air separation plant networks include a number of pipeline distribution systems that connect multiple air separation plants to multiple customers. The air separation plants are known cryogenic distillation columns which typically separate air into oxygen and nitrogen. An auxiliary argon column can be included in such plants to also produce argon products. Liquid products, for instance, liquid oxygen and liquid nitrogen are the premium products in that energy must be expended in liquefaction and further, the liquid is typically distributed over the road by truck.
Determining production allocation of gaseous products feeding the pipeline networks is a complex decision in that the plants differ with respect to production capabilities, efficiencies, product mix and energy costs. The customer demand level is contractually based. Since the flow rate to the customer from any section of the pipeline can be correlated with the pressure measured within the pipeline, air separation production among the various plants is controlled to insure that the required pressure along pipeline sections is maintained.
Since the gas demand can change almost instantaneously, the first goal is to meet gas demand. The second goal is to insure a sufficient liquid inventory is maintained to meet local geographical liquid demand along with any liquid needed for pipeline backup.
While proper gas product allocation is limited to the plants feeding the physical pipeline, the proper decisions regarding liquid production must account for the broader liquid distribution network. Current liquid production decisions are made with the aid of modeling tools to determine the average liquid production requirements for each plant in a given region. The production target is based on current inventory, plant availability, expected energy costs and the region's expected customer demand. The decisions are reviewed daily or weekly and revised as necessary.
While the foregoing approach is adequate to make certain that customer demands are met, it does not necessarily guarantee that operating profits will be maximized. The decisions require a detailed knowledge of the performance and constraints of the plants and pipelines along with the knowledge of both the supplier and customer contracts. Furthermore, the people making the decisions are not available twenty-four hours a day to make and implement the required decisions.
Gas and liquid production needs drive the decisions around energy purchases. Air separation plants are driven by substantial amounts of electricity. In many cases, all or a portion of the required electricity must be purchased a day or more in advance. Once the power has been purchased for the next day, the operation of the particular plant must be done within the constraints of that purchase. Thus proper planning and deciding energy purchases is very important in optimizing the economics of the liquid distribution network. As a result, allocation and distribution decisions are made on short notice, with limited information regarding plant capability and efficiencies. While reasonable decisions are made, it is difficult to make the best decision all the time and profits are compromised.
In a recently published United States Application, Publication Number 20020017113, a method is provided for automatically setting a target level for at least one air separation unit in a network of air separation units. The network is controlled by a control system which generates production target levels that are representative of a network production target level and the network energy usage level. The production target level is one that minimizes the sum of the energy usage levels. The problem with this type of control system is that merely minimizing the energy usage level does not minimize the cost of energy because the cost of energy over a network can vary from plant to plant.
As will be discussed, the present invention provides a method of controlling production within a network or a plurality of air separation plants to produce and distribute liquid for a plurality of customers in such manner as the cost of energy is minimized.